Collaborative Representation for Hyperspectral Anomaly Detection
By Wei Li, Qian Du. IEEE Transactions on Geoscience and Remote Sensing, 2015
672 citations recorded by the source corpus.
Subfields: Atmospheric Science, Computational Mechanics, Media Technology
View Paper: https://www.semanticscholar.org/paper/e39f6313d374531a1b76441b091b897fb6b4272f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atmospheric Science
- Shutao Li
- Jun Yu Li
- Xudong Kang
- Jon Atli Benediktsson
- Antonio J. Plaza
- Kenli Li
- Xiangping Zhang
- Lianru Gao
In Computational Mechanics
- Shutao Li
- Antonio J. Plaza
- Jon Atli Benediktsson
- Xudong Kang
- Jun Yu Li
- Lina Zhuang
- José M. Bioucas-Dias
In Media Technology
- Shutao Li
- Xudong Kang
- Jun Yu Li
- Jon Atli Benediktsson
- Antonio J. Plaza
- Leyuan Fang
- Lianru Gao
- José M. Bioucas-Dias
Citations in the corpus
- Hyperspectral Anomaly Detection With Attribute and Edge-Preserving Filters (2017, methodology): “By contrast, the LRX, SVDD, and CRD methods are all quite time consuming, and thus, hard to be used in real applications.”
- Anomaly Detection in Hyperspectral Images Based on Low-Rank and Sparse Representation (2016, neutral): “The collaborative-representation-based detector is proposed in [21].”
- BockNet: Blind-Block Reconstruction Network With a Guard Window for Hyperspectral Anomaly Detection (2023, background): “[10], SRX_Local [11], CRD [31], CRDBPSW [33], 1 and 2S-GLRT [13] 2 ) and five 1 https://github.com/zephyrhours/Hyperspectral-Anomaly-Detection-CRDBPSW 2 https://github.com/zephyrhours/Hyperspectral-Anomaly-Detection-2S-GLRT global-based methods (i.e., GRX [9], FrFE [12], 3 GAED [49], 4 RGAE [48], 5…”